1. Semantic Wikis for Information Management
Working Group
Conor Shankey
CEO
March 9, 2006
Visual Knowledge, Inc.
4/15/2019

2. Topics Intro to SWIM Intro to Visual Knowledge Quick Overview of Wiki
Semantics?
What do we mean by semantic wiki?
Layering in enterprise information sharing
Definition
Notional architecture
Key capabilities (trust amplifier)
Deployment Characteristics
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3. S.W.I.M. Federal CIO’s council on semantic inter-operability SICoP
Pilot to research and test semantic wiki based solutions
Collaboration, information sharing and reference knowledge
Brand Niemann
Mills Davis
Elisa Kendall
Deborah McGuiness
Conor Shankey
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4. S.W.I.M. Scope of Users All levels of government Individuals
Ad Hoc Groups
Communities of Interest
The public
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5. Motivating Use Cases vs.
2005 Tsunami – rapidly assembled wiki-based global group
Katrina – Conventional multi level command and control
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6. Other Gov’t Semantic Wiki Initiatives
US Patent Office Peer Review Process pilot
meta-tagging pilot to address backlog of 600,000 patents
CIA – white paper on semantic wikis
Building Semantic Webs for e-government with Wiki technology
Christian Wagner,* Karen S.K. Cheung and
Rachael K.F. Ip
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7. Visual Knowledge Conor Shankey
Founder & CEO of Visual Knowledge, 15 years.
Architected largest corporate wan/lan of it’s kind outside US in 1990
Architected enterprise transactional frame system to supplement/replace mission critical mainframe systems of large power utility
CTO/co-founder of several spin out companies from Visual Knowledge
Co-founder Clera Pharmaceuticals, small anti-psychotic drug discovery company
NCOR technical committee, Chair of 2006 OWL workshop (Intl Semantic Web Conference)
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8. Visual Knowledge What is our technology?
Large scale multi-agent software systems
Agents that are rapidly modeled and evolved by millions of people
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9. Visual Knowledge
R&D through real-world implementations
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10. Visual Knowledge What is our technology?
Systems of agents that can be federated and can create executable systems
Agent systems that cope with conflicting ideas, causality and context
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11. The working units of Visual Knowledge
Semantic agent
Atom of knowledge, content, and behavior.
At the most granular level, everything in Visual Knowledge is made up of semantic agents.
Semantic agents are declarative specifications for services. They are not algorithms. Their DNA is knowledge — knowledge about resources, content, media, language, processes, functions, and how to communicate with other agents.
Semantic agents collaborate with other agents across platform(s) to provide services and capabilities.
Semantic agents can be modeled, built, purchased, shared, acquired, and linked together.
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12. Visual Knowledge
Pluggable Packages of Semantic Agent Capability via Web Services
Composite Apps
MOF/ UML/ERD
VK Upper Ontologies
OWL Engine
ISO11179
Meta Meta
Semantic Microkernel
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13. The original wiki idea
“A web site where anybody could create/edit a web page”
Structure
is not pre-determined
invented & evolved by community
neither top down or bottom up
Quick collaborative writing
Non-linear Hypertext
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14. Simplicity Additional Notions Very simple markup for authors
Any page can be immediately revised assuming you have the right privileges
All changes are audited and transparent to the community
“Concepts” in text can immediately become active resources (pages/links)
Simplicity
articles
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15. Benefits of the wiki idea
Distinct concepts or topics are built on the fly
Discourse forms around or in the context of a topic
Eliminates serialized document work flow
Team or community members can immediately see commentary in the context of a topic
Consensus
Agility
Cohesion
Speed
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16. version? Compared To… Each person edits a copy of the document
A poor soul merges the results
Expensive file shares
ing bulky documents
“Versions” of opaque documents everywhere
“Organizing” documents in hierarchal file system
version?
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17. Greatest Strength and Weakness
Topics or concepts lack semantics
A WikiWord is just a WikiWord
A page with related formatted text and WikiWords
Authored, versioned content
Instance based security
Arbitrary structure
Quick and open architecture and adoption led to lack of standardization
Security?
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18. Semantic? (It’s what we do every second of the day.)
Convert data into something we can comprehend
By developing or applying concepts
Quickly relating them to instances in the world
Applying and revising our world models
Sharing our models with others
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19. How do you do semantics? Generalization Aggregation Common Properties
organizing concepts by kind
Aggregation
Aggregating complexes into simpler concepts
Common Properties
Relationships (connecting properties)
Attributes (flat properties)
Naming Conventions
Terms / Phrases
Language
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20. That Sounds like Meta Data?
Very Similar
Meta Data
focuses on serving the implementation paradigms of the system
Is the semantics of the data structures in an information system
System Paradigm
Meta Data
Relational
ERD
Object Oriented
UML
XML Documents
XSD, XMI
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21. Taxonomies and Vocabularies
Close
One hierarchy of terms of concepts
Permit only one accepted notion of a term
Brother?
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22. What else do semantics provide?
Contextual Meaning
Inferred Relationships
Causality
Granularity
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23. Context, …
Water on mars?
Food
Space Exploration
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24. …, How is this relevant to Information Sharing?
In a large agency there are 10,000s of databases
Millions of data elements
Millions of documents
Privacy, Security and Power
Consuming Objectives
…But Wordnet only has ~300,000 concepts
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25. Harmonizing Data Elements to Concepts
PERSON
F_NAME
L_NAME ?
How could semantic wikis help?
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26. Alignment of ontologies?
How could semantic wikis help?
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27. Ontology and MetaData can be Technical
How could semantic wikis help?
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28. But aligning even the simplest models may require human dialog
Water on mars?
Food
Space Exploration
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29. The need Standards agnostic Completely pluggable
Harmonization center for meta data and ontologies
“Soft” wiki layer that invites user collaboration and discourse
Configurable governance
Federated change management
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30. Federated Trust Engines
Meta Data Elements
Reference Knowledge
Ontologies, Taxonomies, Vocabularies
Share More Share Less
More Trust Less Trust
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31. Deployment Characteristics
Community Servers
Enterprise Servers
Team Servers
Semantic Desktops
Light
Agile
Portable
Federated
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32. Who Benefits? Individual Ad Hoc Groups Formal Groups COIs
Organize and access what matters to me
Quickly assimilate
Group authoring
Federated response
Governance
Management
Knowledge Reference
Controlled Publication
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33. Summary Large organizations require a new way to share information
Wikis provide an ideal way to collaborate
Semantic wikis can be used to harmonize ontologies and meta data
Federation, change management, security and governance are essential
If you would like to beta, please contact
4/15/2019